Wireless communication systems, such as the 3rd Generation (3G) of mobile telephone standards and technology, are well known. An example of such 3G standards and technology is the Universal Mobile Telecommunications System (UMTS™), developed by the 3rd Generation Partnership Project (3GPP™) (www.3gpp.org).
The 3rd and 4th generations of wireless communications, and particular systems such as LTE (Long Term Evolution), have generally been developed to support macro-cell mobile phone communications, and more recently femto-cell mobile phone communications. Here the ‘phone’ may be a smart phone, or another mobile or portable communication unit that is linked wirelessly to a network through which calls etc. are connected. Henceforth all these devices will be referred to as mobile communication units. Calls may be data, video, or voice calls, or a combination of these.
Typically, mobile communication units, or User Equipment as they are often referred to in 3G parlance, communicate with a Core Network of the 3G or 4G wireless communication system. This communication is via a Radio Network Subsystem. A wireless communication system typically comprises a plurality of Radio Network Subsystems. Each Radio Network Subsystem comprises one or more cells, to which mobile communication units may attach, and thereby connect to the network. A base station may serve a cell. Each base station may have multiple antennas, each of which serves one sector of the cell.
Operators of wireless communication systems need to know what is happening in the system, with as much precision as possible. A particular issue is the need to solve ‘faults’. Faults may take a wide variety of forms, but can be summarised as events when the network and/or one or more mobile communication units do not perform as expected.
Modern wireless communication systems allow a high degree of autonomy to individual mobile communication units and to base stations. As a consequence, decisions about setting up and ‘tearing down’ call links throughout the network are not all made centrally. As a result, an additional complication arises from the volume of information generated within the wireless communication system. In one day, a wireless communication system may generate 100 gigabytes of data about calls that have been made in the network.
This volume of data has proved a major obstacle to fault location in existing wireless communication systems. In particular, conventional data management techniques have proved to be inadequate for managing such large volumes of data, for example potentially in the billions (1,000 millions) of records or more.
A particular problem encountered by network operators in managing the large volumes of data that they collect is that of efficient and effective retirement of data once it is no longer required and/or when it is necessary to free up space for new data. Such retirement of data is necessary in order to provide some means of limiting the amount of data required to be stored. However implementing such retirement of data, in a manner that does not become a computational burden on the system, is a challenge.
The conventional approach to the retirement of time-stamped data is typically an ‘oldest first’ approach, whereby all data older than a particular time/date is retired. However, such an approach does not take into consideration factors such as the amount of free space that may be available and/or required for new data. Furthermore, such an approach does not enable the retention of different types/categories of data to be prioritised, for example whereby some types/categories of data may advantageously be retained for longer periods of time than other categories of data.